Computational structure-based approach to study chimeric antigens using a new protein scaffold displaying foreign epitopes.

The identification and recombinant production of functional antigens and/or epitopes of pathogens represent a crucial step for the development of an effective protein-based vaccine. Many vaccine targets are outer membrane proteins anchored into the lipidic bilayer through an extended hydrophobic portion making their recombinant production challenging. Moreover, only the extracellular loops, and not the hydrophobic regions, are naturally exposed to the immune system. In this work, the Domain 3 (D3) from Group B Streptococcus (GBS) pilus 2a backbone protein has been identified and engineered to be used as a scaffold for the display of extracellular loops of two Neisseria gonorrhoeae membrane proteins (PorB.1b and OpaB). A computational structure-based approach has been applied to the design of both the scaffold and the model antigens. Once identified the best D3 engineerable site, several different chimeric D3 displaying PorB.1b and OpaB extracellular loops were produced as soluble proteins. Each molecule has been characterized in terms of solubility, stability, and ability to correctly display the foreign epitope. This antigen dissection strategy allowed the identification of most immunogenic extracellular loops of both PorB.1b and OpaB gonococcal antigens. The crystal structure of chimeric D3 displaying PorB.1b immunodominant loop has been obtained confirming that the engineerization did not alter the predicted native structure of this epitope. Taken together, the reported data suggest that D3 is a novel protein scaffold for epitope insertion and display, and a valid alternative to the production of whole membrane protein antigens. Finally, this work describes a generalized computational structure-based approach for the identification, design, and dissection of epitopes in target antigens through chimeric proteins.

Semi-Autonomic AI LF-NMR Sensor for Industrial Prediction of Edible Oil Oxidation Status.

The evaluation of an oil's oxidation status during industrial production is highly important for monitoring the oil's purity and nutritional value during production, transportation, storage, and cooking. The oil and food industry is seeking a real-time, non-destructive, rapid, robust, and low-cost sensor for nutritional oil's material characterization. Towards this goal, a 1H LF-NMR relaxation sensor application based on the chemical and structural profiling of non-oxidized and oxidized oils was developed. This study dealt with a relatively large-scale oil oxidation database, which included crude data of a 1H LF-NMR relaxation curve, and its reconstruction into T1 and T2 spectral fingerprints, self-diffusion coefficient D, and conventional standard chemical test results. This study used a convolutional neural network (CNN) that was trained to classify T2 relaxation curves into three ordinal classes representing three different oil oxidation levels (non-oxidized, partial oxidation, and high level of oxidation). Supervised learning was used on the T2 signals paired with the ground-truth labels of oxidation values as per conventional chemical lab oxidation tests. The test data results (not used for training) show a high classification accuracy (95%). The proposed AI method integrates a large training set, an LF-NMR sensor, and a machine learning program that meets the requirements of the oil and food industry and can be further developed for other applications.

Neisserial adhesin A (NadA) binds human Siglec-5 and Siglec-14 with high affinity and promotes bacterial adhesion/invasion.

Neisserial adhesin A (NadA) is a meningococcal surface protein included as recombinant antigen in 4CMenB, a protein-based vaccine able to induce protective immune responses against Neisseria meningitidis serogroup B (MenB). Although NadA is involved in the adhesion/invasion of epithelial cells and human myeloid cells, its function in meningococcal physiology is still poorly understood. To clarify the role played by NadA in the host-pathogen interaction, we sought to identify its cellular receptors. We screened a protein microarray encompassing 2,846 human and 297 mouse surface/secreted recombinant proteins using recombinant NadA as probe. Efficient NadA binding was revealed on the paired sialic acid-binding immunoglobulin-type lectins receptors 5 and 14 (Siglec-5 and Siglec-14), but not on Siglec-9 therein used as control. The interaction was confirmed by biochemical tools with the determination of the KD value in the order of nanomolar and the identification of the NadA binding site by hydrogen-deuterium exchange coupled to mass spectrometry. The N-terminal domain of the Siglec-5 that recognizes the sialic acid was identified as the NadA binding domain. Intriguingly, exogenously added recombinant soluble Siglecs, including Siglec-9, were found to decorate N. meningitidis surface in a NadA-dependent manner. However, Siglec-5 and Siglec-14 transiently expressed in CHO-K1 cells endorsed NadA binding and increased N. meningitidis adhesion/invasion while Siglec-9 did not. Taken together, Siglec-5 and Siglec-14 satisfy all features of NadA receptors suggesting a possible role of NadA in the acute meningococcal infection.IMPORTANCEBacteria have developed several strategies for cell colonization and immune evasion. Knowledge of the host and pathogen factors involved in these mechanisms is crucial to build efficacious countermoves. Neisserial adhesin A (NadA) is a meningococcal surface protein included in the anti-meningococcus B vaccine 4CMenB, which mediates adhesion to and invasion of epithelial cells. Although NadA has been shown to bind to other cell types, like myeloid and endothelial cells, it still remains orphan of a defined host receptor. We have identified two strong NadA interactors, Siglec-5 and Siglec-14, which are mainly expressed on myeloid cells. This showcases that NadA is an additional and key player among the Neisseria meningitidis factors targeting immune cells. We thus provide novel insights on the strategies exploited by N. meningitidis during the infection process, which can progress to a severe illness and death.